文献类型：期刊文献

英文题名：Improving A* algorithm for path planning of unmanned surface vessels in maritime rescue

作者：Qin, Lei[1];Fang, Yiming[1,2];Lu, Zhikang[1];Gao, Shuang[1,2]

机构：[1]Shaoxing Univ, Sch Mech & Elect Engn, Shaoxing 312000, Peoples R China;[2]Shaoxing Univ, Inst Artificial Intelligence, Shaoxing 312000, Peoples R China

年份：2025

外文期刊名：SHIPS AND OFFSHORE STRUCTURES

收录：SCI-EXPANDED(收录号：WOS:001465546100001)、、EI(收录号：20251618258655)、Scopus(收录号：2-s2.0-105002712712)、WOS

基金：This work was supported by National Natural Science Foundation of China [grant number: 52301379]; the 'Pioneer' and 'Leading Goose' R&D Program of Zhejiang [grant number: 2024C03038].

语种：英文

外文关键词：A* algorithm; global key nodes; redefine neighbour nodes; safety threshold; danger value of the path

外文摘要：Path-planning is the key for marine rescue using unmanned surface vessel. Planning an efficient and safe path can significantly improve the efficiency of marine rescue, and existing path-planning algorithms are prone to collision and grounding with islands and shallows. To address this issue, this paper proposes a method for improving A* algorithm. First, global key nodes were extracted based on maritime map information using image processing techniques. Then, the global key nodes that can be directly reached in a straight line and meet safety threshold were screened as child nodes of current node to participate in the search. Finally, the path was planned by introducing the path danger value into the cost function of A* algorithm to consider the path cost and safety. Simulation results showed that the path planned by improved A* algorithm is safer and smoother than other paths, and the search time and path cost are optimized.